Analyst II, Data Science (R-19484)

The Role

Dun & Bradstreet Technology and Corporate Services India LLP is looking for candidates to support the Data Science team in Trade and Credit Risk Analytics. The candidate needs to work closely with the team based in India and across a range of Analytics leaders who are located globally to fulfill delivery on a timely basis

Key Responsibilities

Work on development of B2B Risk solutions which includes Standard and custom solutions catering to various clients including fortune 500 companies

Work with internal / external D&B clients and stakeholders; Participate in all aspects of a modelling engagement, including design, development, validation, calibration, documentation, approval, implementation, monitoring, and reporting

Applying LLMs, and prompt engineering to analyze large-scale, unstructured and structured B2B datasets (e.g., Company News, Corporate Annual Reports) for credit risk, fraud detection, and compliance.

Design, develop and test new risk signals to effectively identify risk patterns from structured and Unstructured data

Develop AI Agents for business deploying autonomous agents. These agents utilize Machine Learning (ML) and Natural Language Processing (NLP) to detect risk triggers, anomalies in real-time, shifting risk management from reactive reporting to predictive, actionable insights

Ability to work on multiple assignments, many of which with challenging timelines

Ability to work independently, as well as collaborate effectively in a team environment

Partner with internal D&B team to develop new business solutions in risk analytics

Key Skills

What we are looking for

Master’s degree or higher with concentration in a quantitative discipline such as (Math/Stat, Economics, Computer Science, Finance, Operations Research, etc.) with 2 - 5 years of experience in Data Science.

Experience in development of risk models is desirable.

Application of Machine Learning Models using techniques such as Xgboost, Light GBM, Random Forest, Logistic Regression, Decision Tree, Neural Networks etc.,

Strong programming skills with the ability conduct research utilizing Python and Pyspark to manipulate data and conduct statistical analysis.

Strong SQL skills and experience working with large datasets.

Ability to build and maintain relationships with clients.

Ability to effectively communicate complex ideas to both a technical and non-technical audience.

Preferred Skills

• Analytical mind and business acumen, especially in Financial Services Industry.
• Working experience in applying modern machine learning techniques.
• Passionate on stay abreast of cutting-edge ML algorithms, with good grasp of ML explain-ability methods.